Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves

Remote sensing has been applied to map the extent and biophysical properties of mangroves. However, the impact of several critical factors, such as the fractional cover and leaf-to-total area ratio of mangroves, on their canopy reflectance have rarely been reported. In this study, a systematic globa...

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Main Authors: Chunyue Niu, Stuart Phinn, Chris Roelfsema
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/13/2617
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spelling doaj-f26a9327fa944c62a502bbb296a34ee12021-07-15T15:44:41ZengMDPI AGRemote Sensing2072-42922021-07-01132617261710.3390/rs13132617Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of MangrovesChunyue Niu0Stuart Phinn1Chris Roelfsema2Remote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, AustraliaRemote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, AustraliaRemote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, AustraliaRemote sensing has been applied to map the extent and biophysical properties of mangroves. However, the impact of several critical factors, such as the fractional cover and leaf-to-total area ratio of mangroves, on their canopy reflectance have rarely been reported. In this study, a systematic global sensitivity analysis was performed for mangroves based on a one-dimensional canopy reflectance model. Different scenarios such as sparse or dense canopies were set up to evaluate the impact of various biophysical and environmental factors, together with their ranges and probability distributions, on simulated canopy reflectance spectra and selected Sentinel-2A vegetation indices of mangroves. A variance-based method and a density-based method were adopted to compare the computed sensitivity indices. Our results showed that the fractional cover and leaf-to-total area ratio of mangrove crowns were among the most influential factors for all examined scenarios. As for other factors, plant area index and water depth were influential for sparse canopies while leaf biochemical properties and inclination angles were more influential for dense canopies. Therefore, these influential factors may need attention when mapping the biophysical properties of mangroves such as leaf area index. Moreover, a tailored sensitivity analysis is recommended for a specific mapping application as the computed sensitivity indices may be different if a specific input configuration and sensitivity analysis method are adopted.https://www.mdpi.com/2072-4292/13/13/2617global sensitivity analysisPAWNcanopy reflectance modelvegetation index (VI)mangroves
collection DOAJ
language English
format Article
sources DOAJ
author Chunyue Niu
Stuart Phinn
Chris Roelfsema
spellingShingle Chunyue Niu
Stuart Phinn
Chris Roelfsema
Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
Remote Sensing
global sensitivity analysis
PAWN
canopy reflectance model
vegetation index (VI)
mangroves
author_facet Chunyue Niu
Stuart Phinn
Chris Roelfsema
author_sort Chunyue Niu
title Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
title_short Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
title_full Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
title_fullStr Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
title_full_unstemmed Global Sensitivity Analysis for Canopy Reflectance and Vegetation Indices of Mangroves
title_sort global sensitivity analysis for canopy reflectance and vegetation indices of mangroves
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-07-01
description Remote sensing has been applied to map the extent and biophysical properties of mangroves. However, the impact of several critical factors, such as the fractional cover and leaf-to-total area ratio of mangroves, on their canopy reflectance have rarely been reported. In this study, a systematic global sensitivity analysis was performed for mangroves based on a one-dimensional canopy reflectance model. Different scenarios such as sparse or dense canopies were set up to evaluate the impact of various biophysical and environmental factors, together with their ranges and probability distributions, on simulated canopy reflectance spectra and selected Sentinel-2A vegetation indices of mangroves. A variance-based method and a density-based method were adopted to compare the computed sensitivity indices. Our results showed that the fractional cover and leaf-to-total area ratio of mangrove crowns were among the most influential factors for all examined scenarios. As for other factors, plant area index and water depth were influential for sparse canopies while leaf biochemical properties and inclination angles were more influential for dense canopies. Therefore, these influential factors may need attention when mapping the biophysical properties of mangroves such as leaf area index. Moreover, a tailored sensitivity analysis is recommended for a specific mapping application as the computed sensitivity indices may be different if a specific input configuration and sensitivity analysis method are adopted.
topic global sensitivity analysis
PAWN
canopy reflectance model
vegetation index (VI)
mangroves
url https://www.mdpi.com/2072-4292/13/13/2617
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